[NVFuser] Enable E2E BCast-PWise-Reduction fusions (#43129)
Summary:
Had a bunch of merged commits that shouldn't have been there, reverted them to prevent conflicts. Lots of new features, highlights listed below.
**Overall:**
- Enables pointwise fusion, single (but N-D) broadcast -- pointwise fusion, single (but N-D) broadcast -- pointwise -- single (but N-D) reduction fusion.
**Integration:**
- Separate "magic scheduler" logic that takes a fusion and generates code generator schedule
- Reduction fusion scheduling with heuristics closely matching eagermode (unrolling supported, but no vectorize support)
- 2-Stage caching mechanism, one on contiguity, device, type, and operations, the other one is input size->reduction heuristic
**Code Generation:**
- More generic support in code generation for computeAt
- Full rework of loop nest generation and Indexing to more generically handle broadcast operations
- Code generator has automatic kernel launch configuration (including automatic allocation of grid reduction buffers)
- Symbolic (runtime) tilling on grid/block dimensions is supported
- Simplified index generation based on user-defined input contiguity
- Automatic broadcast support (similar to numpy/pytorch semantics)
- Support for compile time constant shared memory buffers
- Parallelized broadcast support (i.e. block reduction -> block broadcast support)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/43129
Reviewed By: mrshenli
Differential Revision: D23162207
Pulled By: soumith
fbshipit-source-id: 16deee4074c64de877eed7c271d6a359927111b2
